With the concurrent rise of artificial intelligence and quantum information science, these two fields are merging in a synergistic manner. In this growing trend, some works try to design new theoretical models based on quantum algorithms to improve classical machine learning for desired quantum speed-up [1]}, [2]}, [3]}, [4]}, [5]}, [6]}, [7]}, [8]}, [9]}, [10]}. At the same time, with the ever-increasing complexity of quantum systems, advanced quantum information technologies also require more powerful tools for data processing and data analysis. Therefore, on the other hand, we urgently need to combine existing classical machine learning techniques to solve practical, but difficult, problems in quantum information science, such as tomography [11]}, [12]}, [13]}, classifying quantum states [14]}, [15]}, [16]}, quantum metrology [17]}, [18]}, [19]} and quantum control [20]}, [21]}, [22]}.
